www.nature.com/scientificreports OPEN Study of the active ingredients and mechanism of Sparganii rhizoma in gastric cancer based on HPLC‑Q‑TOF–MS/MS and network pharmacology Xiaona Lu1,2,3, Yawei Zheng2,3, Fang Wen2, Wenjie Huang2, Xiaoxue Chen2, Shuai Ruan2, Suping Gu2, Yue Hu1,2, Yuhao Teng1,2 & Peng Shu1,2* Sparganii rhizoma (SL) has potential therapeutic efects on gastric cancer (GC), but its main active ingredients and possible anticancer mechanism are still unclear. In this study, we used HPLC‑Q‑TOF– MS/MS to comprehensively analyse the chemical components of the aqueous extract of SL. On this basis, a network pharmacology method incorporating target prediction, gene function annotation, and molecular docking was performed to analyse the identifed compounds, thereby determining the main active ingredients and hub genes of SL in the treatment of GC. Finally, the mRNA and protein expression levels of the hub genes of GC patients were further analysed by the Oncomine, GEPIA, and HPA databases. A total of 41 compounds were identifed from the aqueous extract of SL. Through network analysis, we identifed seven main active ingredients and ten hub genes: acacetin, sanleng acid, ferulic acid, methyl 3,6‑dihydroxy‑2‑[(2‑hydroxyphenyl) ethynyl]benzoate, cafeic acid, adenine nucleoside, azelaic acid and PIK3R1, PIK3CA, SRC, MAPK1, AKT1, HSP90AA1, HRAS, STAT3, FYN, and RHOA. The results indicated that SL might play a role in GC treatment by controlling the PI3K‑ Akt and other signalling pathways to regulate biological processes such as proliferation, apoptosis, migration, and angiogenesis in tumour cells. In conclusion, this study used HPLC‑Q‑TOF–MS/MS combined with a network pharmacology approach to provide an essential reference for identifying the chemical components of SL and its mechanism of action in the treatment of GC. Gastric cancer (GC) is one of the leading causes of cancer-related death worldwide, and its incidence rate is sixth among cancers1. At present, surgery, chemotherapy, and other traditional therapies are the main treatments. How- ever, the incidence of local recurrence and distant metastasis afer gastric cancer surgery is high. Chemotherapy is associated with toxicity and side efects; thus, it is challenging for these treatments to mediate a long-term antitumour efect. Terefore, it is necessary to explore new strategies for the treatment of this disease. In China, traditional Chinese medicine (TCM) is widely used in the treatment of GC and has shown advantages with its multipathway, multitarget, and multilink characteristics, small side efects, and signifcant efcacy. Sparganii rhizoma (SL) is the dried tuber of the Sparganiaceae plant Sparganium stoloniferum (Buch.-Ham. ex Graebn.) Buch.-Ham. ex Juz., which is a traditional Chinese medicine. It has a pungent, bitter, fat attributes and enters the liver and spleen meridians. Its efects include tonifying the blood and promoting qi, removing stagnant food, and alleviating pain. It is included in the Pharmacopoeia of the People’s Republic of China (2015 Edition)2. Previous experiments by our research team suggested that the “Sparganii rhizoma-Curcuma zedoary-Salvia chinensis” herb pair with SL as one of the main components had growth-inhibitory efects on both regular and resistant GC cells, and the inhibitory efect increased with increasing concentration3. Modern pharmacological studies have also shown that SL has an apparent inhibitory efect on the proliferation of GC cells and can pro- mote tumour cell apoptosis4. In addition, some studies have found that the combination of traditional Chinese medicine preparations mainly composed of SL and chemotherapy can prolong the progression-free survival 1Oncology Department, Afliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China. 2First School of Clinical Medicine, Nanjing University of Chinese Medicine, Nanjing, China. 3These authors contributed equally: Xiaona Lu and Yawei Zheng. *email: [email protected] Scientifc Reports | (2021) 11:1905 | https://doi.org/10.1038/s41598-021-81485-0 1 Vol.:(0123456789) www.nature.com/scientificreports/ (PFS) of patients with advanced gastric cancer, improve the quality of life of patients, and reduce the adverse reactions to chemotherapy 5. Although previous studies have shown that SL has potential therapeutic efects on GC, its main active ingredients and possible anticancer mechanism are still unclear. High-performance liquid chromatography coupled with quadrupole time-of-fight mass spectrometry (HPLC-Q-TOF–MS), which is a common qualitative and quantitative analysis technology combining liquid chromatography and mass spectrometry, can be used to analyse the structure of trace components in crude substances without a reference substance6. Both positive and negative ionization modes have been used to con- frm the related chemical compounds and their characteristic fragment ions according to the accurate molecular mass information of the excimer ion peaks and the fragment ions. Ten, compounds are ultimately determined by comparisons with the relevant database. HPLC-Q-TOF–MS/MS is characterized by high resolution, high sensitivity, high selectivity, short response time, wide scanning range, high molecular mass accuracy, and an ability to obtain multistage mass spectrum fragment information for compounds. It can quickly analyse and identify the structures of complex substances such as TCM and is very convenient for basic research on TCM materials7,8. Network pharmacology is a method for predicting the pharmacological mechanism of drug treat- ments for diseases based on the theory of systems biology and the use of complex biological network models, starting from the integrity and systematic nature of interactions among drugs, chemical components, targets, and diseases9,10. Its holistic and systematic characteristics are consistent with the principles of the holistic view, syndrome diferentiation and treatment of TCM, which have been widely used in the study of TCM11,12. For example, Yucheng Guo et al. used a network pharmacology research method to construct a multiscale math- ematical model of infammation-induced tumorigenesis, further identifed the key biological molecular network and genetic interaction module from the dynamic evolution path of infammation and cancer, and predicted the TCM ingredients that can inhibit infammation-induced tumorigenesis. Tis method is of great value for the accurate prevention and treatment of cancer and the modernization of TCM 13,14. Terefore, in this study, HPLC- Q-TOF–MS/MS was used to rapidly analyse and identify the chemical components in SL, and the mechanism of SL in the treatment of GC was explored by combining network pharmacology research methods. Te specifc fowchart is shown in Fig. 1. Results Identifcation of the chemical components of SL. We analysed SL aquatic extract samples based on the above conditions of liquid chromatography and mass spectrometry. We used positive and negative ion mode scanning in this paper to obtain as much information as possible. Te exact mass-to-charge ratio (m/z) of the compound was obtained by TOF–MS, while the second-order fragment ion of this mass number was obtained by product ion secondary mass spectrometry. By using online databases, referring to the relevant literature and considering the fragmentation rule of compounds, we qualitatively analysed the structures of SL-related compounds. Forty-one compounds were ultimately identifed: nine phenylpropanoids, eight organic acids, four favonoids, four amino acids, two alkaloids, and fourteen other compounds. Te secondary mass spectra of each compound are shown in the “Supplementary Figures”. Table 1 shows the retention time, mass spectrometry information, and related references of the identifed compounds. Network pharmacology analysis. Prediction of potential targets of compounds and collection of targets for GC. SwissTargetPrediction predicted a total of 1157 potential targets of the 41 compounds identifed by mass spectrometry, and we obtained 471 afer removing duplicate targets (Supplementary Table S1). We retrieved data from the GeneCards, OMIM, DisGeNET, and TTD databases and identifed 2670, 542, 634, and 3 GC-related targets afer screening, respectively, which resulted in 3225 targets afer merging and removal of duplicate targets (Supplementary Table S2) (Fig. 2a). Potential mapping of the targets of compounds resulted in a total of 262 common targets with those related to GC, which were ultimately identifed as target genes of SL for the treatment of GC (Fig. 2b). Compound‑target network analysis. We established a compound-target network with 262 GC target genes as anticancer targets (Fig. 3). Tere are 294 nodes and 685 edges in the network, among which the 32 green nodes represent the main components of SL, the 262 orange nodes represent the targets of GC, and the 685 edges represent the interactions between the components and the targets of GC. By observing the network, we found that the same active ingredient can act on multiple targets. Te same target also corresponds to diferent chemi- cal components, which fully refect the multicomponent and multitarget characteristics of SL in GC treatment. According to the network topological parameters, the average values of the degree and betweenness centrality of compound nodes were 21.40625 and 0.076039366, respectively. We screened out compounds with a degree and betweenness centrality greater than the mean, such as acacetin, sanleng acid, ferulic acid, methyl 3.6-dihydroxy- 2-[(2-hydroxyphenyl)